But with Tuesday’s election results, the investment divide between blue, purple and red states has grown even more pronounced.

So far this year, less than 2% of all startup investment has gone to companies in post-election red states, defined as those that will have both a Republican governor and two Republican U.S. senators.

The red states’ share is much smaller than in years’ past due to five states shifting to purple. Of those, the largest venture hub is Texas, which shifted to purple with the election of Democratic Senator James Talarico and Governor Gina Hinojosa, followed by Ohio.

This year, as of Election Day, startups in the remaining 17 red states 1, which are home to nearly a quarter of Americans, had collectively in venture funding, with Florida, Tennessee and Utah among the largest contributors. To put that in perspective: It’s less than the typical nationwide total in a single week.

Purple states rising

The 10 purple U.S. states2, meanwhile, are home to just over a quarter of Americans and pulled in about $28.6 billion this year as of Election Day. That’s much higher than the red state tally, but still less than 6% of all U.S. startup funding.

Beyond the aforementioned newcomers Texas and Ohio, several other purple states regularly pull in sizable venture funding, including Pennsylvania, North Carolina and to some extent Wisconsin.

Also worth noting: The divide between red, purple and blue states is somewhat less stark when it comes to round counts. About 12% of startup financings of $1 million or more went to purple state companies this year, and about 9% went to red states.

Broadly, it looks like backers are still finding plenty of investment-worthy talent outside of blue states when it comes to smaller deals. However, they are concentrating most of their capital into big AI rounds for California and New York companies.

Blue states get over 90% of startup funding

This brings us to our next point: Blue states receive the overwhelming majority of startup funding, of which most goes to California.3

Per a Crunchbase analysis last week, California companies had pulled in more than three-fourths of all U.S. startup funding in 2026. Most of that stems from mega-financings for San Francisco-based and.

While no other state comes close to California for attracting investment, the nearest runners up are also predominantly blue states, including New York and Massachusetts. In total, blue states have pulled in a staggering $481 billion in startup investment this year as of Election Day, per Crunchbase data, a new record.

Politics and what makes for a venture hub

So is it politics, or coincidence?

Broadly speaking, the qualities that geographic startup hubs share — such as a deep tech talent pool, urban environs, leading tech companies and top research universities — aren’t specifically the domain of blue states. That said, predominantly rural states, which tend to lean red, are less likely to have those ingredients.

Even so, there’s no rule against red state startup prowess. Austin, for example, managed to cement its status as a major tech hub even while Texas remained solidly under Republican control. And Utah also boasts a sophisticated startup scene.

But following a Democratic electoral sweep, it’s hardly a surprise that more startup hubs now find themselves located in blue or purple states.

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• California Startups Have Raised More So Far In 2026 Than The Entire US Ever Has In A Single Year
• Austin’s Star Is Still Shining Bright: Venture ������Ƶ City’s Startups Hits All-Time High
• Only 2 States Saw Their Share Of US Venture Funding Rise Last Year

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was 16 and had been repeatedly hospitalized for Graves’ disease when her mother suggested they move to China and become monks. Frustrated with the care her daughter was receiving through Medicaid, she wanted to try something different.

Chen left high school and spent about two years as a monk, ordained in the United States before spending several months at a monastery in China. She meditated, reread the same books, and gradually felt well enough to consider returning to school.

She went on to enter without a high school diploma, briefly play video games professionally, and become an engineer at . When she quit that job, she didn’t have a startup idea. She just wanted to find work she believed in.

That mission eventually led her to ,” a Philadelphia-based company that’s building software for some of the government’s least glamorous tasks, including administering school food services and managing public records.

After her brief stint at a large tech company, Chen realized she wanted to tackle the everyday problems that make people’s lives harder, even if solving them wouldn’t generate much excitement in Silicon Valley.

“What does it actually take to solve the really unsexy, boring stuff?” she remembers asking herself.

A different route to college

Before Chen was thinking about government software, she was trying to get well enough to return to school.

At the monastery in China, she meditated, ate food grown on-site or brought by nearby villagers, and lived without internet access. She continued taking thyroid medication and said her health became more manageable during that period.

She also read. A lot. With no nearby place to buy books, she reread the ones she had brought, finding different places around the monastery to sit with them.

Her attachment to those books prompted a conversation with a fellow monk who asked what she enjoyed about reading and where she might find more books. The discussion eventually turned to colleges, and why she wasn’t attending one.

Chen explained her health problems. He observed that she seemed well. She realized she was.

So Chen returned to the U.S., homeschooled herself and enrolled at Colorado College without having earned a high school diploma. She turned 20 during her freshman year and graduated in 2019 with a double major in mathematics and economics.

While she was in college, Chen briefly played Dota 2 professionally. She also played against ’s game-playing bots, an early encounter with AI technology she would later help support as an engineer.

After an initial job in Boston, she joined Facebook, where she built infrastructure used to train AI models.

Leaving without a startup idea

Then on Jan. 6, 2021, Chen was attending a remote company all-hands meeting while watching coverage of the attack on the U.S. Capitol on another screen. Her concerns about Facebook’s role in enabling the organization of violence made her question whether she could continue working there.

“I realized that I couldn’t work for Big Tech anymore,” she recalls.

She quit shortly afterward.

To figure out her next move, she returned to the sort of questions she had encountered as a monk. What made her happy? What mattered to her? What was she good at?

Programming remained her most concrete skill. She just needed to figure out where to apply it.

An introduction through , a student-run accelerator focused on nontraditional founders, connected her with , a venture firm that has backed the likes of and . The firm wrote Chen her first check in 2021, before she had even settled on the business that would become FSH.

Although she didn’t have a developed company pitch, Chen’s earnest explanation of what motivated her and her passion for solving a meaningful problem won investors over. That investment gave her room to experiment, she said.

FSH took shape into what it is today in 2024. The Contrary investor who first backed her, , has since joined the company as its chief operating officer.

The company has raised $25 million in total funding, including a recent $20 million Series A that Chen said came together in about a week. Participants in that raise included , , Ramp, , , . Contrary also led its seed financing.

Finding the problem beneath the paperwork

Ultimately, Chen landed on government software because in her view, it had the potential to solve many consequential problems that attracted relatively little excitement.

For example, permits, licenses, grant applications and other administrative processes can be slow for reasons that extend beyond an outdated interface, Chen noted. Information may exist in separate departments. Updating a website may require approvals from multiple stakeholders including policymakers, communications staff and an IT team.

Putting a chatbot on top of that system, Chen argues, leaves much of the underlying problem unresolved.

Her approach to solving some of the problems that exist within governments draws on an exchange she had years earlier at the monastery, where one of her chores was feeding koi.

The head monk would periodically ask her if she thought she was the fish or the pond?

Initially, Chen didn’t understand what he was asking. But he kept returning to the question, and she began thinking about it. Eventually, she picked a fish she thought resembled her: one that stayed out of fights, swam with the group and occasionally ventured off on its own.

The head monk’s response was, “You’re the pond, not the fish.”

Chen viewed the exchange as a lesson in looking beyond individual pieces to understand how a whole system works. Looking at government software, she believed that it meant examining why information is scattered or processes are slow before deciding what technology to build.

One early area for FSH has been K-12 food services, where administrators must perform tasks such as coordinating meal planning, nutritional information and reimbursement requirements. Another is records and archive management, including the paper documents that can still require residents to visit a government office to retrieve them.

FSH does use AI for tasks such as optical character recognition, translation and natural-language search. But, Chen said, the company treats it as a tool within its software, rather than relying on a chatbot or an AI agent to handle an entire process.

Government sales have required patience. The company generated less than $100,000 in revenue in its first year, Chen said, reflecting the time it takes to win contracts. At the time of this interview, FSH had roughly eight or nine employees, with additional offers outstanding.

Thinking slowly, moving quickly

Chen’s time as a monk has also influenced how she runs the company.

She admits she is skeptical of startup culture that treats sleeping in the office or working extremely long hours as evidence of commitment or a badge of pride. Rather, Chen views some of that behavior as performative, especially when it comes at the expense of the rest that she believes people need to work effectively.

Her preferred motto to the team is, “Slow is smooth and smooth is fast.”

“We think slowly about a lot of things, and then we do things quickly,” she said.

Chen believes it’s crucial to first understand the people, departments and procedures behind a government service before trying to improve it.

Looking back, Chen also credits her success to finding people willing to back someone whose experience didn’t resemble the usual résumé. That includes the college that admitted her without a high school diploma and an investor who wrote a check before she had settled on a company idea.

“You definitely end up finding your own way if you just stick to being weird,” she said.

Related Crunchbase query:

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European AI-focused startups raised $23 billion in the first half of 2026, up 130% year over year and accounting for 55% of the region’s venture funding, according to a joint Crunchbase and HumanX . That investment surge is sharpening a question at the heart of the sovereign AI debate: Where should countries concentrate their resources to capture the technology’s economic value and retain control over their data?

But sovereignty does not require owning every layer of the AI stack, according to two executives I spoke with onstage at the conference: founder and CEO and , ’s chief product and technology officer.

Their perspectives from Europe and the United Arab Emirates, respectively, pointed to opportunities in specialized chips and applications and underscored how purchasing decisions, government mandates and access to computing power can determine whether AI ambitions translate into growth.

Five-layered cake

, CEO and president of chip giant , has detailed a “” to deliver AI that includes  energy, chips, infrastructure, models and applications.

For Del Maffeo, whose company develops chips for inference, the opportunity lies in the semiconductor layer, as more AI processing moves beyond centralized data centers and onto devices.

“Artificial intelligence will expand from cloud computing, from centralized data centers, to devices closer to us in the physical world,” he said. “To enable this, you need specific chips which can run efficiently, at a lower cost, to connect these networks that today are running in the cloud. We are here to solve this problem.”

Five-year-old Axelera AI has two generations of chips it sells to around 600 customers. The company next plans to expand to products for decentralized cloud computing.

AI transformation

Abu Dhabi-based AI71 partners with large organizations and government agencies to help them benefit from AI transformations.

The United Arab Emirates has the largest compute per capita in the world and has a three-month mandate for every government agency to set up agentic processes for its citizens, according to Ghissassi. Energy is abundant and cheap. Over the next two years, the goal is to reach half of every citizen’s interactions with the government with an AI agent, he said.

Competing at the model layer does not make sense, said Ghissassi. He believes there will be two, three or four companies that can afford to be in the race, given the amount of capital required and the fact that it commoditizes very quickly.

The application layer is the one that is really important, for sovereignty where you want to own your data, said Ghissassi, who previously led product development at . “You want to make sure that it stays with you, be it that you’re a government or an enterprise. If you’re giving away your trade secrets and know-how, nobody stops whoever is being a provider to you today, from replacing you.”

In the UAE, “what helps is the mandate, the pace at which things happen, the availability of compute, both in terms of sovereign clouds, or on-prem, or global clouds, and then the amount of capital that is being invested to help transform these companies to benefit from these technologies,” Ghissassi said.

By contrast, Europe struggles as it is a net importer of energy. It has strengths in the semiconductor industry but lacks all the real compute for AI, in neural networks and frontier labs.

“We should not be obsessed with controlling the entire stack,” said Del Maffeo. In Europe we have to create value instead of just paying for a service, he added. “Creating value means creating a wealthy economy.”

Europe’s strengths include its large pools of research talent and its population of 440 million people who can benefit from AI. However, the culture of large businesses purchasing from startups is less established, meaning it doesn’t have the same flywheel for growth seen in the U.S., said Del Maffeo.

“What worries me is that we are a little bit lagging behind, and therefore we are missing this value creation, and this will weaken the economies of Europe,” he said.

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• Europe Posted Its Strongest Venture Funding Quarter In 4 Years As UK Gains, M&A Holds Up

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A decade ago, Espahbodi co-founded aerospace and defense startup accelerator and moved back to the U.S. to expand it. On the advice of friends at , he opened an office in El Segundo, California, near , just as more alumni of that company were leaving to launch hard-tech startups of their own and next-generation defense startups including were emerging.

Espahbodi eventually sold his stake in Starburst and launched , which invests in companies spanning industrial infrastructure, manufacturing, energy and water desalination. The firm has backed 14 companies since making its first investment in January 2023.

He also advises federal agencies on working with nontraditional, venture-backed companies. In an interview with Crunchbase News, he discusses how AI is changing hardware economics, why software investors are rushing into industrial technology, and what he believes many of them misunderstand about the sector.

This interview has been edited for length and clarity.

Crunchbase News: What led you to leave Starburst and launch Generational Partners?

Espahbodi: About four years ago, I noticed that my friends from SpaceX were leaving the space vertical and moving horizontally across physical industries. I reached an inflection point: I didn’t want to remain locked into the space sector. I wanted to follow my friends.

I sold my equity in the accelerator, and part of the investment team left with me to start Generational Partners. For the past four years, we’ve invested in what you might call the SpaceX-mafia and hard-tech sectors — anything involving industrial infrastructure, manufacturing, energy or water desalination.

We made our first investment in January 2023, in a North Dakota-based drone company. It was a trial by fire and an opportunity to prove the thesis. We’ve invested in 14 companies since then.

You were already investing in physical, safety-critical industries before the generative AI boom. Has AI materially changed where you invest, or has it mainly reinforced your existing thesis?

Espahbodi: I tend to arrive earlier than others. I embraced the idea that hardware does not have to be capital-intensive. People often confuse hard tech with deep tech, but nomenclature aside, you don’t need to invest in science to win in these categories.

AI has dramatically changed that narrative and encouraged more people to get on board. I’m not looking to invest in science. I don’t necessarily see opportunities in quantum computing, nuclear fusion or other technologies being spun out of laboratories.

People who worked at companies such as SpaceX, and laid their companies’ foundations digitally. AI has significantly improved that augmentation and performance, enabling these companies to tackle legacy industries more aggressively and, more importantly, with new business models.

Another major component of the AI question is that frontier labs have become more expensive and capital-intensive than traditional hardware companies. The success of frontier AI labs, combined with the SpaceX IPO becoming an enormous wealth-creation event, creates a new environment. It raises questions about what is truly capital-intensive, what makes a product or its intellectual property defensible, and where companies are reengineering products around different business models.

Hardware has historically been capital-intensive, slower to commercialize and difficult to scale. Under what conditions does its technical defensibility compensate for those challenges?

Espahbodi: Fundamentally, it comes down to the business model. I look for creative software talent combined with commoditized hardware, significant customer demand and a new business model.

One of our portfolio companies was founded by the team that built the factory for user terminals. When you buy a retail Starlink antenna, these people built and scaled the assembly line that produced it at high volume.

While deploying those terminals globally to provide internet access, they observed that poverty often stemmed from a lack of access to clean water. They asked whether they could replicate the proliferated satellite-and-user-terminal architecture for edge water desalination.

Rather than investing in multibillion-dollar, nation-state infrastructure like that used by Gulf countries, they wanted to mass-produce every component in a vertically integrated stack. Their goal was to produce a cooler-sized device that could clean water at the point of need.

used a digital, software-based approach to build the bill of materials needed for mass manufacturing. AI is part of its business and operations, but the company’s real innovation was inverting the infrastructure model and scaling it.

I helped Vital Lyfe win its first customers within the and . Those organizations can use its devices in the field rather than shipping pallets of bottled water by air freight. That created a signal for overseas partnerships and nonprofit humanitarian-aid applications. It showed that there could be a different way to provide clean water.

Those are the kinds of unique business models that excite me.

What other companies founded by SpaceX alumni demonstrate how hardware businesses can overcome the traditional challenges of the sector? What can these founders build today that would have been difficult five years ago?

Espahbodi: Another example is the team SpaceX recruited to build the autonomous drone ships that catch boosters in the middle of the ocean. The team included former Coast Guard personnel and oil-and-gas technicians.

At SpaceX, they had the freedom to use software and AI tools to automate station-keeping — the ability of those drone ships to position and navigate themselves and reach the right location.

That team spun out and brought in many former colleagues to change commercial maritime shipping. They retrofit legacy boats operating in harbors and waterways and move supply-chain goods.

They brought a digital-first foundation to automating the controls on tugboats and barges. That had never existed before because the communications link to those ships didn’t exist. Starlink changed the concept of operations. The company can use its software expertise to change how physical devices operate aboard these boats and allow their sensors to send signals anywhere in the world.

That makes it possible to retrofit and overhaul how legacy shipping vessels navigate harbors and waterways in the U.S. It’s another example of SpaceX alumni applying the playbook and technologies they learned at SpaceX to a much broader commercial industry.

You’ve said AI is eroding traditional software moats. What evidence are you seeing that investors are responding by moving into hardware and industrial technology?

Espahbodi: I meet many software investors who feel they’re missing out on hardware but don’t necessarily understand it. I’ve met beauty investors who now say they’re defense-tech investors.

Los Angeles is a hotbed of firms that historically invested in software, media or consumer packaged goods. But people forget that Southern California, particularly El Segundo, is the aerospace capital of the world and has the largest concentration of mechanical-engineering talent.

Across the region — from China Lake to San Diego — technicians, builders and vocational talent are intersecting with the democratization of software and access to AI tools. Many local VCs have never taken advantage of the hardware talent located around them, so they’re being thrown for a loop.

Ironically, Bay Area VCs have been among those leaning most heavily into this. But it’s happening everywhere. I’m in Washington, D.C., now, and one of the first investors in , the hypersonic missile company, was in Virginia — before and others became involved.

Los Angeles VCs in particular know there is a talent war underway and that many people are leaving established companies to launch new businesses in these categories. But they struggle to underwrite those deals. They don’t know how to distinguish a strong opportunity from fear of missing out or something merely cosmetic.

So investors’ lack of experience in the space isn’t deterring them from writing checks or competing for deals?

Espahbodi: You have to ask why. The answer is their limited partners.

Sophisticated allocators, such as endowments, foundations and pension funds, along with more FOMO-driven family offices and high-net-worth investors, are watching this wave of SpaceX, and Anduril alumni create new companies and raise extraordinary rounds.

Many of those companies are no longer raising solely to pursue intellectual property. They’re building war chests to acquire other companies. The lines between private equity and venture capital are blurring. VC-backed companies are doing private equity-style buyouts, while venture deals are bringing in private equity checks.

That leaves LPs pushing for more. The success of the frontier AI labs has also perpetuated a fear of a “SaaS apocalypse,” which I don’t think is real — although I sometimes question ’s 1 stock price for fun.

It creates what venture does best: tourists and FOMO. LPs ask why their managers aren’t investing in the same companies and how they can participate, raise more money and show that they aren’t missing out. That’s how I’ve seen investors unfamiliar with these sectors enter the market.

Some of the largest Silicon Valley firms … missed this dynamism wave. Now they’re leaning in hard, sometimes at ridiculous valuations for companies that have yet to produce anything.

If more venture funding continues to flow into defense, aerospace and industrial technology, what prevents hardware from developing the same problems software experienced, including too many competing companies?

Espahbodi: Bring it on — hard and fast, and as much as possible.

Venture as a category exists because it was always about hardware. I would argue that the SaaS era, from the dot-com boom until now, was a blip compared with what venture was originally intended to underwrite.

I would move away from the hardware-vs.-software distinction and ask who is reframing the business model. Is there a way to reengineer a combination of software and hardware to unlock customer value? That’s the more important question.

How important is geography for these startups? Does locating near a major government customer help a company win contracts, and how do startups navigate procurement if they aren’t based near Washington, D.C.?

Espahbodi: It’s a common misconception that Washington is where the money is. The Los Angeles Air Force Base houses , which is another way of saying it holds ’s wallet. El Segundo makes the purchasing decisions for the fastest-growing portion of the military budget.

Washington is a place of considerable activity that needs to be influenced. Venture has never had this degree of influence on an administration and its executive orders. We’re also seeing portfolio companies backed by influential investors win government contracts worth as much as $1 billion at a time. That’s extraordinary.

Geographically, companies need to be where the talent is as much as where the customers are. Government customers should signal what matters, but companies shouldn’t organize themselves entirely around the government.

My catchphrase is that I want everyone to be commercially focused but mission-aware. I don’t want them to be mission-focused on the government. I want government to signal what it cares about while companies remain commercially focused.

The talent war for this convergence of hardware and digital technology is centered in Southern California. If you aren’t building and recruiting there, you’re falling behind. I like that the Bay Area is trying to attract more hardware talent and capitalize on the automotive and humanoid-robotics markets.

But I think the talent base for the factory of the future starts in Southern California and can then be used as a model for expansion into other places, as companies such as Anduril have done in Ohio and Louisiana.

We invested in a company founded by people from SpaceX and . They immediately moved to Austin to build a smart factory for raw-material processing. They wanted to automate the process at its source.

The largest concentration of cotton farming is around Lubbock in the Texas Panhandle. The company is building automated factories from the ground up to mill cotton into yarn and then complete the digital, vertically integrated stack by producing textiles at prices that beat outsourcing to China, Vietnam and other countries.

It sounds crazy, but the founder is determined to do it. If you can prove the model in textiles, you can apply it to copper. If you can do it with copper, you can do it in pharmaceuticals. From there, it could go in any direction.

Do startups located near Space Systems Command have an advantage?

Espahbodi: Not for that reason alone. The advantage is that they’re part of the ecosystem and geography. They’re spending time in the same bars and restaurants, and their children attend the same schools. They’re witnessing the same velocity.

Space Force itself is facing greater demand than ever to protect assets in space. Whatever happens with funding for individual programs, it remains the fastest-growing portion of the Pentagon budget.

I don’t think startups should locate there solely to be close to the customer. They should be there for the talent they need to build.

Related Crunchbase queries:

Related reading:

• Sector Snapshot: Space Tech Startup Funding Orbits New Highs
• Sector Snapshot: Defense Startup Funding Hits An All-Time Record As VCs Begin To Eye Exits

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

It was not a holiday week on the funding front, as a raft of largely AI-focused companies closed big rounds. The largest of these was a $1.5 billion financing to enterprise AI startup and a Series D for meal and delivery provider . The week also included some big financings for enterprise tech, food delivery, drones and construction automation.

1. , $1.5B, enterprise AI tools: Fireworks AI, a developer of tools for enterprises to turn “general-purpose models into specialized intelligence trained on their own data,” raised $1.505 billion in Series D funding. , and led the financing, which set a $17.5 billion valuation for the San Mateo, California-based company.

2. , $650M, meals and delivery: Wonder, an operator of kitchens and meal delivery services, closed on $650 million in Series D funding at a $9 billion pre-money valuation. Capital will go in part toward expanding operations for the New York-based company, which currently has 140 locations.

3. , $400M, life sciences AI: AI drug discovery startup Chai Discovery secured $400 million in Series C funding at a $3.8 billion valuation. led the financing, investing alongside , , and others.

4. , $300M, robots: Cambridge, Massachusetts-based Walden Robotics, a startup building general-purpose robots for work in manufacturing and logistics, launched out of stealth with $300 million in funding. and led the round, which values the company at $1.1 billion.

5. , $125M, drones: Seattle-based Brinc, a developer of drones for use in public safety and emergency operations, raised $125 million in fresh funding. led the financing, with participation from , and founder and CEO .

6. (tied) , $100M, construction automation: Austin-based TerraFirma, a developer of AI-enabled software and autonomous robotics technology for the construction industry, landed $100 million in new funding, bringing total investment to date to $115 million.

6. (tied) , $100M, enterprise AI: Spectro Cloud, a provider of AI infrastructure management software, said it raised more than $100 million in a Series D round led by . The financing brings total capital raised by San Jose-based Spectro Cloud to $260 million.

8. , $80M, defense tech: Singularity, a startup focused on developing air defense technology, emerged from stealth with $80 million in Series A funding. and 1 led the financing, which set a $400 million valuation for the Los Angeles-based company.

9. (tied) , $70M, fintech: San-Francisco-based fintech startup Flex, a private banking platform for high-net-worth business owners, raised $70 million in a Series B1 financing led by . The round follows the company’s $60 million Series B in December.

9. (tied) , $70M, AI and policy: State Affairs, an AI platform for policy and regulation, secured $70 million in Series A funding led by Khosla Ventures and .

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of July 11-17. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

Illustration:

This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

This week, most of the largest U.S. startup funding rounds centered around the sector one would suspect: artificial intelligence. This was true for the week’s largest venture financing, a $1.5 billion Series F for AI inference technology provider , as well as a majority of rounds in the Top 10. Beyond that, the next-biggest area for startup funding was biotech.

1. , $1.5B, AI inference technology: Baseten, a provider of systems software to run AI applications workloads, raised $1.5 billion in Series F funding, its fourth fundraise in 18 months. , , , and co-led the round, which set a $13 billion valuation for the San Francisco-based company.

2. , $1B, digital marketing: AppsFlyer, a San Francisco-based provider of data analytics with digital marketing as a core use case, reportedly secured more than $1 billion in a Series E funding round at a post-money valuation of $2.7 billion. Backers reportedly include , , and .

3. , $650M, AI inference technology: San Francisco-based Groq closed on $650 million in new funding led by and that it says will be used to scale its AI inference cloud technology and infrastructure. The investment comes just over six months after an acquihire-type transaction in which hired away its founder and key team members and licensed its technology.

4. , $330M, ophthalmic therapies: Ollin Biosciences, a developer of therapies for vision-threatening diseases, picked up $330 million in Series B funding. and led the financing for the Austin-based company.

5. , $320M, foundational AI: General Intuition, developer of a foundational AI model based on gameplay, secured $320 million in Series A funding at a $2.3 billion valuation. led the financing for the New York-based company, while backers including and participated.

6. , $250M, government software: Peregrine Technologies, provider of a platform used by public safety agencies and other government entities, secured $250 million in Series D financing. , , , , and led the financing, which set a $6.8 billion valuation for the San Francisco-based company.

7. (tied) , $200M, risk intelligence: Palo Alto, California-based Quantifind, developer of a risk intelligence platform for financial crime detection and national security operations, closed on $200 million in growth financing led by .

7. (tied) , $200M, foundational AI: San Francisco-based Mirendil, a frontier lab building systems that excel at AI R&D, says it raised a seed round of $200 million led by and . The startup also counts as a backer.

9. (tied) , $190M, AI infrastructure: AI networking infrastructure startup Upscale AI raised $190 million in Series A extension funding, bringing total financing to $500 million. led the round, which set a $2 billion valuation for the Santa Clara, California-based company.

9. (tied) , $190M, biotech: San Francisco-based Osanni Bio, a therapeutics platform focused on ophthalmic therapies and other treatments, secured $190 million in Series B funding led by .

Large non-US deals:

The week also brought some large European rounds:

, $569M, defense tech: Berlin-based defense tech startup Stark reportedly raised $569 million in a financing led by and .

, $546M, insurance: Paris-based health insurance startup Alan secured $460 million in new investment in primary and secondary equity led by .

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of June 18-26. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

Illustration:

During his tenure as chair from 1987 to 2006, Greenspan was renowned for his cryptic utterances on the economy, leaving rate-watchers befuddled as to whether they presaged a likely cut or hike. His wife, veteran correspondent , famously that their marriage took time because “he claims he proposed three times before I was able to understand. He was so oblique. It was like his testimony.”

In spite of his long history of obfuscation, however, Greenspan is best known for a fairly unambiguous two-word phrase: “irrational exuberance.” He coined it in a 1996 to the  , a conservative-leaning think tank, titled “The Challenge of Central Banking in a Democratic Society.”

One of the speech’s core points was the notion that pricing logic in an industrial economy dominated by durable goods and materials is far simpler than for a modern economy increasingly dominated by software and services.

“What is the price of a unit of software or a legal opinion? How does one evaluate the price change of a cataract operation over a 10-year period when the nature of the procedure and its impact on the patient changes so radically?” he mused, before turning to that most famous insight.

That insight, if I am translating Greenspan-speak correctly, was linked to the question of how one can establish long-term confidence in valuations of assets tied to fast-changing technologies and business models, like software, where prior notions of unit economics no longer applied.

“How do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions,” he wondered. It’s a conjecture that 30 years later still has no obvious answer.

Notably, Greenspan’s speech actually predated the most heated periods of the dot-com boom, bubble and implosion, which began in the late 1990s and culminated with the hitting its cyclical peak in early 2000. During and shortly after that period, money-losing e-commerce companies like online grocer and pet supply retailer famously went public at then sky-high valuations before abruptly shuttering. Internet infrastructure providers fared even worse, exemplified by networking equipment maker going from Canada’s most valuable company to penny stock in a couple years.

But while losers lost big, winners eventually eclipsed them. Dot-com-era megastars and , for instance, are now worth nearly $8 trillion combined.

That brings us to one of Greenspan’s other well-known analogies: the lottery ticket.

In Congressional testimony in early 1999, pressed for his thoughts on then fast-rising share prices of hot internet companies, the Fed chair the stock-buying frenzy to playing the lottery. He observed that people have long been willing to pay more for a lottery ticket than their chances of winning would justify, simply because they are drawn to the remote chance of a huge win.

”And undoubtedly some of these small companies, which have stock prices going through the roof, will succeed and they very well may justify even higher prices,” he said. ”The vast majority are almost sure to fail. That’s the way the markets work in this regard.”

Fast-forward to today, and one is easily drawn to apply Greenspan’s analogy to the current AI mania. Once again, we’re seeing unprecedented valuations attached to money-losing companies, many in still relatively nascent stages of development.

In other ways, however, this time it’s not a dot-com lottery ticket redo. For one thing, the companies in which a retail investor might be buying said ticket are by no means small. , at its current market cap, is the sixth-most valuable U.S. public company. It’s priced like a winner, not a wanna-be.

Same holds true for recent valuations for and , both of which have confidentially filed for public offerings likely to debut in coming months. Anthropic hit a $965 billion post-money valuation, while OpenAI’s was recently around $852 billion.

One wonders what Greenspan would say about these stratospheric asset price levels. I’d suspect there are better than lottery-ticket odds that it would be something cryptic.

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Photo: Dr. Alan Greenspan, former Chairman of the Board of Governors of the Federal Reserve, speaks at the Per Jacobsson Foundation Lecture, October 21, 2007, in Washington, DC. (Photo by International Monetary Fund Photograph/Stephen Jaffe used under the .)

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Although the number of women-owned businesses keeps growing, startups led by women continue to fall behind their male counterparts when it comes to raising venture funding.

That’s why former executive teamed up with , a veteran and marketing executive, to found , an -registered, funding portal.

The platform, also called AQi, gives women-led businesses — those that are at least 50% women-owned — a way to raise capital through , a securities framework aimed at opening up startup investing.

Launched in 2024, AQi seeks to help female entrepreneurs reach everyday investors by simplifying regulatory disclosures and business documentation. As a member of the , the platform has passed a rigorous federal vetting process and agrees to operate under strict oversight to protect investors and ensure transparency.

Crunchbase News recently spoke with Huyck and Konwinski to hear more about what led them to start AQi, why they think women don’t need to give up board seats early on, and how they want to help female entrepreneurs raise and hold on to more equity.

This interview has been edited for clarity and brevity.

Crunchbase News: What is your platform’s mission and what led you to launch this company?

Huyck: I spent 21 years at PayPal, where I mentored women through a partnership with the . It was there I learned about the $5 trillion gap in global GDP resulting from women entrepreneurs lacking access to capital.

In the U.S., while women start nearly half of all businesses, they receive only 2% of venture capital and less than 20% of small business loans. I wanted to build an innovative system to solve this. I considered starting a fund, but many already exist. Instead, I wanted to create a crowdfunding platform exclusively for women, providing an additional avenue to raise money. The economic irony is that women entrepreneurs earn 78 cents for every dollar invested, compared to 31 cents for men. It simply didn’t make sense, and I wanted to build a system that truly enables women.

Konwinski: To add to that, we are a very distinct entity. We are not a broker-dealer; we are an SEC-registered and FINRA-member crowdfunding platform. Following the 2012 JOBS Act, Reg CF (Regulation Crowdfunding) was created to allow nonaccredited investors to invest in private, early-stage companies. There are about 50 active platforms in the U.S., but we are the only one founded by women, owned by women, and exclusively serving women-owned businesses.

Beyond just providing a neutral platform, we act as a “quarterback.” We help entrepreneurs navigate the process — whether they are just starting or ready for a “glow-up” — by providing access to accountants, lawyers and marketing firms. We are creating a community where women can get the resources they need to build their businesses without competing for attention in male-dominated tech circles.

How does your platform differ from sites like ?

Konwinski: Kickstarter and are for charitable gifting. We are not asking for charity; we are facilitating investments. We are on par with platforms like or , but our fee structure is more founder-friendly. On platforms like Kickstarter, you might only keep about 60% of the funds raised. Our success fee is only 6.5%. When investors invest in these businesses, they receive equity in return. Furthermore, there is a clear social return: Studies show that for every dollar a woman earns in her business, she creates significant economic benefit for her community and family.

How many businesses have you helped raise capital for thus far?

Huyck: We spent our first year building the technology and another six months on the rigorous SEC and FINRA registration process. We believe this high level of regulation is critical to ensuring investor trust. We currently have a pipeline of 20 businesses. We closed our first campaign earlier this month and have two more launching in the coming weeks.

Since Reg CF has a $5 million cap per 12-month period, how do you position yourselves for high-growth startups? And do you view this as a permanent alternative to traditional venture capital, or a bridge?

Huyck: I don’t see the VC space changing soon because it is heavily reliant on “pattern matching,” where investors look for people and paths that resemble previous successes. Until that breaks, women founders face significant barriers. Crowdfunding is a vital, viable alternative.

Konwinski: I would challenge the notion that $5 million isn’t enough. For many of the companies we work with, that is a strong runway for 18 to 24 months. Because Reg CF allows for rolling raises, a company can raise up to $5 million every 12 months. We see companies use this to reach a significant milestone and then potentially pursue a Series A later. We aren’t trying to be a broker-dealer for Series A deals. We are here for those who get “ghosted” by VCs or don’t want to leverage their homes to secure an SBA loan.

Does a distributed ownership structure with many unaccredited investors create a “messy” cap table that scares off traditional VCs?

Huyck: We utilize special-purpose vehicles. This consolidates all Reg CF investors into a single line item on the company’s cap table, often with a lead investor managing voting rights. This keeps the cap table clean.

Konwinski: Additionally, one of the greatest benefits of our model is that founders retain autonomy. VCs often demand board seats, veto rights and up to 20% equity. With us, founders usually give up only 5%-10% equity, allowing them to maintain control of the company they built from the ground up.

Without the pressure of a VC board, how do you help founders maintain operational discipline? And what do exit horizons look like?

Konwinski: Women entrepreneurs are natural “hustlers” who are inherently self-motivated. They are also excellent at collaborating and leveraging their community rather than operating with ego. Many of the founders we work with are Gen X, balancing business with family, and they have developed an incredible ability to multitask and execute.

Huyck: We also encourage founders to bring on advisers rather than giving up board seats too early. As for exit strategies, many women founders are mission-driven and haven’t historically been forced to consider an exit. We provide the guidance to help them think through those horizons — whether that’s acquisition or long-term growth — so they can make informed decisions rather than being forced into a timeline by traditional VC pressure.

Finally, how does your platform compare to other equity crowdfunding sites like Wefunder?

Konwinski: It is apples-to-apples in terms of our SEC/FINRA licensing. Where we differ is our value proposition: we provide a “concierge” service. On many larger platforms, you are processed through an AI-driven, automated checklist. We are building relationships, talking to our founders, and acting as their partner throughout the process.

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“I recognized both the massive potential AI brought to the tax world, as well as the risks to firms and clients by making mistakes and hallucinations,” he told Crunchbase News.

The accounting industry has historically been slow to adopt new technologies. As of today, the majority of small to mid-sized accounting firms — which make up 90% of the market — remain stuck in a cycle of manual data entry.

Addressing both the opportunities — and risks — that came with advances in AI, Haase started building , a tax prep automation startup, on the side in 2023. Rather than targeting the self-prep market, like does, or the mega-enterprise firms that can afford $15,000-per-return software, Juno was built for the underserved SMB accounting firm.

“We continuously ‘dog fed’ the early Juno prototypes into the firm to see what worked best, what slowed things down, and to make it the most efficient tax preparation platform as possible,” Haase said.

It took about a year and a half just to build integrations. “We had to do a bunch of hacky things to be able to work with the existing tax software,” he explained, “because your typical tax software is actually around 15 to 20 years old and they don’t have public APIs.”

By 2024, Juno had launched a co-pilot. Then, in July 2025, it had a tax product. The startup began onboarding other tax firms, growing to nearly 500 customers over the past year. Last year, Haase sold his accounting firm to focus on growing Juno full-time.

Today, he’s announcing that San Diego-based Juno has raised $12 million in a seed funding round led by , including participation from and .

AI to help humans ‘be the advisers they were trained to be’

What makes Juno different from others in the market, Haase believes, is that it operates on the premise that, at least for the foreseeable future, human tax preparers should be the ones driving the tax-return preparation process.

“A business or high-net-worth tax return requires hundreds of calculations, edge cases, deductions and more,” said Haase, who holds an MBA from . “AI simply can’t do that with the 100% accuracy required not to get audited or charged with tax fraud.”

Describing much of the manual work that most accountants must perform to complete returns as extremely tedious, Haase acknowledges that it’s also very easy for accountants to make mistakes that could prove very costly.

“In school, if you get a 93, an A, you get all the credits,” he said. “But on a tax return, if you have a 99%, you fail, and your client could pay the price in penalties.”

In a nutshell, Juno acts as the bridge between a client’s raw documents and the accountant’s filing software. It performs tasks like pulling data from IRS forms and even unstructured documents, such as business financial statements. Overall, it automates 90% of data entry across more than 90 document types while also flagging prior-year changes and inconsistencies for human validation.

The result is that a process that typically takes a human two to three hours is shrunk down to seven to 10 minutes, Haase estimates.

“We do 95% of a tax return in minutes, leaving the accountant to handle the strategic human decisions — the parts that actually save the client money,” he said.

While he declined to reveal hard revenue figures, Haase said that in just eight months, Juno grew to mid-seven-figure annual recurring revenue.

The startup sells on a per-return basis, starting around $45, dropping to the low $30s for high-volume firms.

‘s recent move into consumer taxes and OpenAI’s hiring of a tax director show that the bigger players are eyeing the tax market. But Haase doesn’t feel threatened.

“High-wealth individuals want assurance. If you’re paying $40,000 in taxes, you don’t want to ‘cross your fingers with a chatbot,” he said. “You want a human to talk to, someone who understands the context of your life.”

Juno isn’t trying to replace accountants, he added.

“It’s trying to rescue them from the data-entry basement so they can actually be the advisers they were trained to be,” Haase said.

The startup plans to roll out business returns soon, a move that Haase expects will significantly scale its customer base.

‘A huge, obvious pain point’

, co-founder and managing director of Bonfire Ventures, said he was drawn to invest in Juno because he believes the company is going after “a huge, obvious pain point in a category that hasn’t been meaningfully modernized in a long time.”

“The workflow pain is real, the labor dynamics make the timing right, and Dave brought exactly the kind of founder-market fit you hope to see,” Andelman told Crunchbase News via email. “He lived this problem before he built the company. That always matters.”

The investor believes that tax prep is a category where trust is crucial to product success.

“If you’re going to bring AI into that workflow, it has to be transparent, auditable, and built with a human in the loop,” Andelman added. “That’s what Juno understood early, and I think that’s a big part of why the product is resonating.”

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per Crunchbase . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

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Founders spend a lot of time thinking about capital. They model burn carefully. They negotiate valuation. They weigh hiring plans against runway.

But many startups overlook a source of capital that doesn’t require dilution at all: tax credits. And to be clear, this isn’t typically because a business doesn’t qualify. It’s because no one builds a process to identify and capture these credits consistently.

Most startups are aware of at least one major opportunity, and that’s the Research & Development tax credit. But fewer founders take a broader look at business decisions throughout the year and how many of those may lead to tax credit opportunities. Hiring decisions, benefit structures, accessibility upgrades, facility investments and certain energy projects all can carry incentives.

So, the issue isn’t eligibility. It’s ownership, timing and consistency.

In early-stage companies, finance teams are lean. Credits often get discussed once a year during tax preparation. However, by that point, it can be too late. The required elections may have been missed, documentation may not support a claim, or deadlines may have passed.

When that happens, the opportunity is gone. We see this pattern frequently in examples such as:

• A company hires several employees who may have qualified for a hiring credit, but no screening process was in place at onboarding.
• A retirement plan is launched without evaluating available startup or employer contribution credits.
• Paid leave policies are expanded without reviewing whether a federal credit applies.
• A facility upgrade is completed without considering whether accessibility- or energy-related incentives were available before the project was placed in service.

None of the above decisions are inherently wrong, but they are incomplete.

Coordinating credits

Tax credits don’t appear automatically because money was spent. Taking advantage requires planning, including specific documentation, elections and coordination between departments. Without that coordination, even well-managed startups leave savings unclaimed.

More-mature companies approach this differently.

Instead of waiting until year-end to ask, “Did we qualify for anything?” established organizations build periodic reviews into their operating cadence.

• Hiring processes include the necessary steps to preserve potential credits.
• Engineering teams track qualifying activities as projects progress.
• Finance evaluates larger operational investments before contracts are finalized.

This doesn’t mean turning every department into tax specialists. It requires clarity around who’s responsible for asking the question early enough, and it ideally includes expert guidance and support to get it right.

It’s helpful to think about this as an evolution.

At a reactive stage — which is most startups — credits are evaluated only when the tax return is being prepared. At a more structured stage, the company reviews credit opportunities quarterly and aligns documentation throughout the year. And in a strategic stage, leadership fully understands how certain business decisions may create incentives and ensures the right processes are in place before those decisions are implemented.

Multiple credits add up

The accumulated financial impact can be meaningful. While a single credit isn’t likely to transform a business, multiple credits across hiring, development and benefits can offset real costs. For companies focused on extending runway without raising additional capital, those offsets matter.

There’s also a governance component.

Investors and buyers increasingly review operational controls during diligence. A startup that has evaluated available credits and maintained documentation signals discipline. A company that hasn’t considered them at all may invite additional questions (especially if elections were missed or filings need to be amended).

None of this is to suggest credits should drive a founder’s core strategy. Product development, revenue growth and customer demand remain the priority. But when companies are already investing in innovation, hiring and infrastructure, it makes sense to evaluate whether part of that investment can be recovered.

The first step is simple: Get the full picture before making any decisions. In many cases, that includes working with an adviser who understands how credits apply to growing businesses.

Then, assign ownership. Determine who is responsible for reviewing credit opportunities throughout the year. Coordinate among departments like finance, HR and operations before major decisions are finalized. Make documentation part of the process rather than a reconstruction exercise at the end of the year.

Being proactive

Again, tax credits are not automatic. They’re for those who plan the entire year.

Startups looking to be more proactive should keep credits like the R&D in mind for its potentially meaningful offsets when investing in product or technical improvements. But don’t stop there.

If considering structured paid leave, review the Paid Family and Medical Leave Credit, which can apply when policies meet specific requirements. Businesses reviewing facility improvements may qualify for the Disabled Access Credit. While credits such as these don’t apply to every company, they’re common enough to demand attention before decisions are finalized — even seemingly unrelated ones.

Startups focused on capital efficiency will see this planning make a measurable difference over time.

is a tax supervisor specializing in research and development tax credits at . He holds a master of science in accounting from and has experience across both public and private sectors. Garba has spent several years advising companies on R&D tax credits, helping startups and growth-stage businesses navigate complex tax regulations and maximize available incentives.

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• Sales And Use Tax: What Every High-Growth Startup Should Know About Compliance
• How Your Startup Can Take Advantage Of The R&D Tax Credit

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